Independent from the still ongoing research in measuring individual
intelligence, we anticipate and provide a framework for measuring collective
intelligence. Collective intelligence refers to the idea that several
individuals can collaborate in order to achieve high levels of intelligence...
present thus some ideas on how the intelligence of a group can be measured and
simulate such tests. We will however focus here on groups of artificial
intelligence agents (i.e., machines). We will explore how a group of agents is
able to choose the appropriate problem and to specialize for a variety of
tasks. This is a feature which is an important contributor to the increase of
intelligence in a group (apart from the addition of more agents and the
improvement due to common decision making). Our results reveal some interesting
results about how (collective) intelligence can be modeled, about how
collective intelligence tests can be designed and about the underlying dynamics
of collective intelligence. As it will be useful for our simulations, we
provide also some improvements of the threshold allocation model originally
used in the area of swarm intelligence but further generalized here.